1863 AN ANALYSIS OF VARIABILTY OF LEARNING CURVE, MARGIN STATUS AND EARLY POST OPERATIVE OUTCOMES IN 1200 ROBOT ASSISTED LAPAROSCOPIC PROSTATECTOMIES IN A MULTI-USER CENTRE

Real-time assessment of learning curve for robot-assisted laparoscopic prostatectomy

INTRODUCTION

The learning curves analysed to date for robot-assisted laparoscopic prostatectomy are based on arbitrary cut-offs of the total cases.

METHODS

We analysed a large dataset of robot-assisted laparoscopic prostatectomies from a single centre between 2008 and 2019 for assessment of the learning curve for perioperative outcomes with respect to time and individual cases.

RESULTS

A total of 1,406 patients were evaluated, with mean operative time 198.08 minutes and mean console time 161.05 minutes. A plot of operative time and console time showed an initial decline followed by a near-constant phase. The inflection points were detected at 1,398 days (308th case) for operative time and 1,470 days (324th case) for console time, with a declining trend of 8.83 minutes and 7.07 minutes, respectively, per quarter-year (p<0.001). Mean estimated blood loss showed a 70.04% reduction between the start (214.76ml) and end (64.35ml) (p<0.001). The complication rate did not vary with respect to time (p=0.188) or the number of procedures (p=0.354). There was insufficient evidence to claim that the number of operations (p=0.326), D'Amico classification (p=0.114 for intermediate versus low; p=0.158 for high versus low) or time (p=0.114) was associated with the odds of positive surgical margins.

CONCLUSIONS

It takes about 300 cases and nearly 4 years to standardise operative and console times, with a requirement of around 80 cases per annum for a single surgical team in the initial years to optimise the outcomes of robot-assisted laparoscopic prostatectomy.

[Ablative therapy in urology: Good practice and perspective]

INTRODUCTION

To expose the main point of discussion from present ablative therapies' guidelines and propose global perspectives.

MATERIALS AND METHODS

A review of the scientific literature was performed in Medline database (http://www.ncbi.nlm.nih.gov) and Embase (http://www.embase.com/) using different associations of keywords "ablative therapy" ; "prostate cancer"; "kidney cancer"; "guidelines"; "hybrid operating room". Publications obtained were selected based on methodology, language and relevance.

RESULTS

Present guidelines on ablative therapies in urology are, considering authors and organs, either particularly prudent (EAU guidelines for prostate and kidney) or relatively optimistic (CIRSE guidelines). This discrepancy is related to a low level of proof. So, a new approach is mandatory: more homogeneous in methodology, and especially more open to a new organization sparing economic efficiency. The objective will be to get multifunctional and multidisciplinaries platforms, in facts and in minds. It will induce, in the future, a deep reflection about training and boundaries' specialties.

CONCLUSION

Ablative therapies represent a crucial stake for urology and a clear example of medicosurgical evolution in future, based on new technologies (energy, robotic, imaging). A serious and deep reflection is necessary to prepare it and be deeply involved in.

Learning curves for urological procedures: a systematic review

OBJECTIVE

To determine the number of cases a urological surgeon must complete to achieve proficiency for various urological procedures.

PATIENT AND METHODS

The MEDLINE, EMBASE and PsycINFO databases were systematically searched for studies published up to December 2011. Studies pertaining to learning curves of urological procedures were included. Two reviewers independently identified potentially relevant articles. Procedure name, statistical analysis, procedure setting, number of participants, outcomes and learning curves were analysed.

RESULTS

Forty-four studies described the learning curve for different urological procedures. The learning curve for open radical prostatectomy ranged from 250 to 1000 cases and for laparoscopic radical prostatectomy from 200 to 750 cases. The learning curve for robot-assisted laparoscopic prostatectomy (RALP) has been reported to be 40 procedures as a minimum number. Robot-assisted radical cystectomy has a documented learning curve of 16-30 cases, depending on which outcome variable is measured. Irrespective of previous laparoscopic experience, there is a significant reduction in operating time (P = 0.008), estimated blood loss (P = 0.008) and complication rates (P = 0.042) after 100 RALPs.

CONCLUSIONS

The available literature can act as a guide to the learning curves of trainee urologists. Although the learning curve may vary among individual surgeons, a consensus should exist for the minimum number of cases to achieve proficiency. The complexities associated with defining procedural competence are vast. The majority of learning curve trials have focused on the latest surgical techniques and there is a paucity of data pertaining to basic urological procedures.